Sentence Similarity
sentence-transformers
Safetensors
Turkish
modernbert
feature-extraction
turkish
mteb
text-embeddings-inference
Instructions to use moganai/MoganBERT-Embed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use moganai/MoganBERT-Embed with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("moganai/MoganBERT-Embed") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
| { | |
| "additional_special_tokens": [ | |
| "[unused0]", | |
| "[unused1]", | |
| "[unused2]", | |
| "[unused3]", | |
| "[unused4]", | |
| "[unused5]", | |
| "[unused6]", | |
| "[unused7]", | |
| "[unused8]", | |
| "[unused9]", | |
| "[unused10]", | |
| "[unused11]", | |
| "[unused12]", | |
| "[unused13]", | |
| "[unused14]", | |
| "[unused15]" | |
| ], | |
| "cls_token": "[CLS]", | |
| "eos_token": "[EOS]", | |
| "mask_token": { | |
| "content": "[MASK]", | |
| "lstrip": true, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false | |
| }, | |
| "pad_token": "[PAD]", | |
| "sep_token": "[SEP]", | |
| "unk_token": "[UNK]" | |
| } | |